Quantitative Analysis of Smooth Progression in Traffic Signal Systems

Beak, Byungho; Head, Larry; Khosravi, Sara

doi:10.1061/jtepbs.0000123

Cited by 12 publications

(21 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Compared with the existing works (2,(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22), more practical and emerged variables are covered in the proposed Bi-PCD. In addition, a new probabilistic surrogate quantification combined with an offset optimization is proposed to improve coordination performances.…”

Section: Methodsmentioning

confidence: 99%

“…Constraints of PCD Visualization (15). There are two essential components in the widely implemented original PCD for an offline optimization (16,17).…”

Section: System Uncertaintiesmentioning

confidence: 99%

“…The second, detector location of fixed detectors, might also impact arrival events for both physical advanced detectors (11,23) and probe vehicle-based virtual detectors (2,12). This is because the arrival events could be affected by a vehicle queue that grows beyond the fixed detector location, thus causing visualization bias which cannot detect arrivals (15). (2,12).…”

Section: System Uncertaintiesmentioning

confidence: 99%

See 2 more Smart Citations

Platoon Priority Visualization Modeling and Optimization for Signal Coordination in the Connected Vehicle Environment

Qiu

Seraj

et al. 2019

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

Although connected vehicle (CV)-based signal coordination has some proposed prototypes and has been investigated by several different strategies, the existing works have issues that require attention, including additional CV-based system uncertainties and platoon priority request considerations. Thus, a generalized framework consisting of a platoon-based bicyclic coordination diagram (Bi-PCD), a new probabilistic surrogate quantification, and a platoon priority-based offset optimization in the CV environment is proposed to improve the coordination performance. The proposed Bi-PCD extends the scope of the current Purdue coordination diagram (PCD) and its variants by covering extra practical and emerged variables. A prototype and field tests in a CV test pilot for general scenarios were implemented in a typical arterial road to verify performances of the proposed Bi-PCD and the offset optimization method. Field results demonstrated that using Bi-PCD could obtain explicit platoon features in both limited and full CV penetration conditions. The comprehensive analysis showed that the proposed Bi-PCD and the platoon priority-based offset optimization could further improve performances of the signal coordination.

show abstract

Section: Methodsmentioning

confidence: 99%

“…Constraints of PCD Visualization (15). There are two essential components in the widely implemented original PCD for an offline optimization (16,17).…”

Section: System Uncertaintiesmentioning

confidence: 99%

Section: System Uncertaintiesmentioning

confidence: 99%

See 1 more Smart Citation

Platoon Priority Visualization Modeling and Optimization for Signal Coordination in the Connected Vehicle Environment

Qiu

Seraj

et al. 2019

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

show abstract

“…Researchers were predominately focusing on how the performance of currently deployed adaptive traffic signal systems can be improved by using enhanced algorithms based on richer data provided by the connected vehicles (21,22). Rare attempts were made to define innovative signal performance quantifiers (23). Assuming full information availability (100% Market Penetration Rate [MPR] of Connected Vechicles [CV] technology), Beak et al conducted an analysis on vehicles' speed variation along a corridor (23).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Rare attempts were made to define innovative signal performance quantifiers (23). Assuming full information availability (100% Market Penetration Rate [MPR] of Connected Vechicles [CV] technology), Beak et al conducted an analysis on vehicles' speed variation along a corridor (23). The outcome of the study was a new signal performance MOE, named Smoothness of the Flow of Traffic (SOFT), which, based on the speed profile, observed determined how smoothly vehicles were traveling along a corridor.…”

Section: Literature Reviewmentioning

confidence: 99%

Comprehensive Framework for Quantitative Performance Assessment of Signal Control Effectiveness using Vehicle Trajectories

Ostojic

Mittal

Mahmassani

2020

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

Connected environments offer more information, improved data availability and quality which can lead to better decision making; new meaningful information adds new functionalities and opportunities to advance operational efficiency. Can traffic signal system efficiency and mobility be measured and enhanced in innovative and meaningful ways by combining two data sources - connected vehicle-generated and controller event logs? This paper develops a comprehensive signal systems performance assessment framework that aims to offer better understanding of current traffic signal practices and standards and add new functionalities and opportunities to enhance signal systems operations. Its core is a novel performance metric that provides a holistic representation of the system which traditional metrics do not offer. To develop and demonstrate the concept, the study used simulation data in a format that corresponds to high resolution data (signal status and vehicle positions) on a tenth of a second level. Vehicle trajectory information is processed, fused with control data, synthesized to produce "information" required to develop a signalized approach performance estimation method. The data analysis platform presented in this study is intended to comprehensively characterize the state of the signalized system and help identify causes of inferior intersection performance by defining a set of visual and quantitative success indicators. The practicality of this method is reflected in reducing the time and effort required by the existing signal design/retiming practice, since trajectory-signal signatures distinguish between incidents and retiming opportunities caused by changing traffic conditions.

show abstract

An optimization model for arterial coordination control based on sampled vehicle trajectories: The STREAM model

Yao

Tan

Tang

2019

Transportation Research Part C: Emerging Technologies

View full text Add to dashboard Cite

Quantitative Analysis of Smooth Progression in Traffic Signal Systems

Cited by 12 publications

References 13 publications

Platoon Priority Visualization Modeling and Optimization for Signal Coordination in the Connected Vehicle Environment

Platoon Priority Visualization Modeling and Optimization for Signal Coordination in the Connected Vehicle Environment

Comprehensive Framework for Quantitative Performance Assessment of Signal Control Effectiveness using Vehicle Trajectories

An optimization model for arterial coordination control based on sampled vehicle trajectories: The STREAM model

Contact Info

Product

Resources

About